A Statistical Evaluation of Multiplicative Congruential Random Number Generators with Modulus 2 31 - 1

Fishman, George S.; Moore, Louis R.

doi:10.2307/2287778

Cited by 59 publications

(20 citation statements)

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“…It is evident that the testing allows critically evaluating the efficiency of three different random number algorithms from a spatial simulation perspective, even if it is not an exhaustive alternative to the wide range of existing uniform generator tests (Fishman and Moore, 1982;Fishman and Moore, 1985;Hopkins, 1983;Knuth, 1981;Marsaglia, 1972).…”

Section: Some Practical Resultsmentioning

confidence: 99%

Convergence of realization-based statistics to model-based statistics for the LU unconditional simulation algorithm: some numerical tests

Iaco

Palma

2002

Stochastic Environmental Research and Risk Assessment (SERRA)

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In geostatistics, stochastic simulation is often used either as an improved interpolation algorithm or as a measure of the spatial uncertainty. Hence, it is crucial to assess how fast realization-based statistics converge towards model-based statistics (i.e. histogram, variogram) since in theory such a match is guaranteed only on average over a number of realizations. This can be strongly affected by the random number generator being used. Moreover, the usual assumption of independence among simulated realizations of a random process may be affected by the random number generator used. Simulation results, obtained by using three different random number generators implemented in Geostatistical Software Library (GSLib), are compared. Some practical aspects are pointed out and some suggestions are given to users of the unconditional LU simulation method.

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Section: Some Practical Resultsmentioning

confidence: 99%

Convergence of realization-based statistics to model-based statistics for the LU unconditional simulation algorithm: some numerical tests

Iaco

Palma

2002

Stochastic Environmental Research and Risk Assessment (SERRA)

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“…The uniform deviate uses a prime modulus multiplicative generator with modulus 213' -1 and multiplier 397204094 (Fishman and Moore, 1982;Tukey, 1977). Non-fathers were matched to teen fathers two to one.…”

Section: Methodsmentioning

confidence: 99%

The Educational Antecedents of Teen Fatherhood

Dearden

Hale

Álvarez

1992

Brit J of Edu Psychol

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In attempting to identify the determinants of teen pregnancy, researchers have focused on risk factors for young women, largely ignoring teen fathers. This study examines the educational antecedents of teen fatherhood using the 1958 National Child Development Study. Results suggest that those less than 20 years old at onset of fatherhood are much more likely than those who had not fathered a child by age 23 to have experienced academic difficulties and that such difficulties antedate teen fatherhood by as much as a decade. Variables measuring parents' lack of interest in their sons' education were strongly associated with the risk of teen fatherhood as were teachers' negative assessment of boys' academic ability, and the boys' own desire to terminate education as early as possible. Social class was modestly important in explaining differences in educational experiences for teen fathers and non-fathers.

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“…For each replicate k, we generated a unique seed as the integer part of a random number uniformly distributed over the interval (0, 1) using the SAS RANUNI function (Fishman and Moore 1982), multiplied by a million. The replicate seeds were used to generate the permanent random numbers assigned to all enterprises in the frame population at time 0 (2009) and to the new enterprises in the frame population at time 1 (2010).…”

Section: Simulation Study Designmentioning

confidence: 99%

On Precision in Estimates of Change over Time where Samples are Positively Coordinated by Permanent Random Numbers

Lindblom

2014

Journal of Official Statistics

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Measures of period-to-period change are key statistics for many economy surveys. To improve the precision of these estimates of change, the majority of the business surveys at Statistics Sweden select stratified simple random samples (STSI) at different points in time, ensuring positive correlation between samples (overlapping samples) by using permanent random numbers (PRN). Statistics Sweden normally selects positively coordinated STSIs drawn from an updated Business Register (BR). In these samples, the industry strata are usually stratified further within industry into size strata. When the most recent sampling frame contains updated classification variables for all units, enterprises can change stratum between two sampling occasions. A drawback of the coordinated sample selection procedure is that the desired correlation between the two samples decreases if the proportion of enterprises that change strata is substantial. Consequently, the sample design must anticipate the potential effect of stratum changes between samples. This article presents a study that examines how the design of a repeated business survey affects the precision in estimates of change over time using the Turnover in the Service Sector survey conducted by Statistics Sweden as an example.

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A Statistical Evaluation of Multiplicative Congruential Random Number Generators with Modulus 2 31 - 1

Cited by 59 publications

References 0 publications

Convergence of realization-based statistics to model-based statistics for the LU unconditional simulation algorithm: some numerical tests

Convergence of realization-based statistics to model-based statistics for the LU unconditional simulation algorithm: some numerical tests

The Educational Antecedents of Teen Fatherhood

On Precision in Estimates of Change over Time where Samples are Positively Coordinated by Permanent Random Numbers

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